A Convenient High-Yield Room-Temerature Synthesis of Mixed Tri(Amino) Silanes by Transmination of Tris(Dicyclohexylamino) Silane And-Their Characterization

Tris(dicyclohexylamino)silane. (DCA)3SiH. is prepared by the reaction of trichlorosilane with dicyclohexylamine. This is found to undergo transamination reactions with other secondary amines (R2NH). such as pyrrolidine, piperidine, hexamethyleneimine. morpholine. N-methylpiperazine and diethylamine to yield mixed tri(amino)silanes of the formula (DCA)(R2N)2SiH in quantitative yields. These new derivatives are found to be moisture sensitive and hydrolyze to yield their respective amines, hydrogen and silica. They are found to be stable in an inert atmosphere. They have been characterized by IR, NMR (H-1, Si-29), mass spectroscopy and CHN analysis. N-15 NMR for one of the compounds has been done.

Nestedness pattern in stream diatom assemblages of central Western Ghats

Community diversity and the population abundance of a particular group of species are controlled by immediate environment, inter-and intra-species interactions, landscape conditions, historical events and evolutionary processes. Nestedness is a measure of order in an ecological system, referring to the order in which the number of species is related to area or other factors. In this study we have studied the nestedness pattern in stream diatom assemblages in 24 stream sites of central Western Ghats, and report 98 taxa from the streams of central Western Ghats region. The communities show highly significant nested pattern. The Mantel test of matrix revealed a strong relationship between species assemblages and environmental conditions at the sites. A significant relationship between species assemblage and environmental condition was observed. Principal component analysis (PCA) indicated that environmental conditions differed markedly across the sampling sites, with the first three components explaining 78% of variance. Species composition of diatoms is significantly correlated with environmental distance across geographical extent. The current pattern suggests that micro-environment at regional levels influences the species composition of epilithic diatoms in streams. The nestedness shown by the diatom community was highly significant, even though it had a high proportion of idiosyncratic species, characterized with high numbers of cosmopolitan species, whereas the nested species were dominated by endemic species. PCA identifies ionic parameters and nutrients as the major features which determine the characteristics of the sampling sites. Hence the local water quality parameters are the major factors in deciding the diatom species assemblages.

Chemical Degradation of Poly(styrene disulfide) and Poly(styrene tetrasulfide) by Triphenylphosphine

The chemical degradation of polysulfide polymers, viz., poly(styrene disulfide), PSD, and poly(styrene tetrasulfide), PST, has been achieved using triphenylphosphine, TPP. The reaction was monitored using P-31 NMR spectroscopy. The solubility analysis of the reaction residues reveals that while PSD degrades completely, PST on the other hand, undergoes complete degradation only when the concentration of TPP is increased. Moreover, the reaction of PST with TPP occurs at room temperature whereas PSD requires a higher temperature. The reaction products were analyzed using the direct pyrolysis mass spectrometric (DP-MS) technique, and their formation has been explained through an ionic mechanism.

Controlled synthesis of CuO nanostructures on Cu foil, rod and grid

CuO nanowires are synthesized by heating Cu foil, rod and grid in ambient without employing a catalyst or gas flow at temperatures ranging from 400 to 800 degrees C for a duration of 1-12 h. Scanning electron microscopy (SEM) investigation reveals the formation of nanowires. The structure, morphology and phase of the as-synthesized nanowires are analyzed by various techniques such as X-ray diffraction (XRD), transmission electron microscopy (TEM), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA) and Fourier transform infrared spectroscopy (FTIR). It is found that these nanowires are composed of CuO phase and the underlying film is of Cu2O. A systematic study is carried out to find the possibilities for the transformation of one phase to another completely. A possible growth mechanism for the nanowires is also discussed. (C) 2011 Elsevier B.V. All rights reserved.

Multivariate nonlinear ensemble prediction of daily chaotic rainfall with climate inputs

The basic characteristic of a chaotic system is its sensitivity to the infinitesimal changes in its initial conditions. A limit to predictability in chaotic system arises mainly due to this sensitivity and also due to the ineffectiveness of the model to reveal the underlying dynamics of the system. In the present study, an attempt is made to quantify these uncertainties involved and thereby improve the predictability by adopting a multivariate nonlinear ensemble prediction. Daily rainfall data of Malaprabha basin, India for the period 1955-2000 is used for the study. It is found to exhibit a low dimensional chaotic nature with the dimension varying from 5 to 7. A multivariate phase space is generated, considering a climate data set of 16 variables. The chaotic nature of each of these variables is confirmed using false nearest neighbor method. The redundancy, if any, of this atmospheric data set is further removed by employing principal component analysis (PCA) method and thereby reducing it to eight principal components (PCs). This multivariate series (rainfall along with eight PCs) is found to exhibit a low dimensional chaotic nature with dimension 10. Nonlinear prediction employing local approximation method is done using univariate series (rainfall alone) and multivariate series for different combinations of embedding dimensions and delay times. The uncertainty in initial conditions is thus addressed by reconstructing the phase space using different combinations of parameters. The ensembles generated from multivariate predictions are found to be better than those from univariate predictions. The uncertainty in predictions is decreased or in other words predictability is increased by adopting multivariate nonlinear ensemble prediction. The restriction on predictability of a chaotic series can thus be altered by quantifying the uncertainty in the initial conditions and also by including other possible variables, which may influence the system. (C) 2011 Elsevier B.V. All rights reserved.

Pd-coated Ni nanoparticles by the polyol method: an efficient hydrogenation catalyst

Pd-coated Ni nanoparticles of 50 +/- 15 nm size are prepared by the polyol method and characterized by X-ray diffraction, transmission electron microscopy, X-ray photoelectron spectroscopy and thermogravimetry analysis. Surface coverage of Pd on Ni particles is less than a monolayer for 0.5 and 1 at% Pd-coated Ni. Quantitative conversion of nitrobenzene to aniline is observed over these Pd-coated Ni particles at 27degreesC under one atmospheric pressure of hydrogen. 0.5 and 1 at% Pd-coated Ni exhibits 10 times greater activity than that of typical colloidal palladium and platinum catalysts and 2.5 times higher activity than commercial 5 wt% Pd/C.

Solution processable quinoxaline based molecular materials for organic field effect transistors

Three new solution processable quinoxaline based donor-acceptor-donor (D-A-D) type molecules have been synthesized for application in field effect transistors. These molecules were characterized by UV-visible spectroscopy, thermal gravimetric analysis, differential scanning calorimetry and cyclic voltammetry. DFT calculation gives deeper insight into the electronic structure of these molecules. The crystallinity and morphology features of thin film were investigated using X-ray diffraction. These molecules show liquid crystalline phase confirmed by DSC and optical polarizing microscopy. Investigation of their field effect transistor performance indicated that these molecules exhibited p-type mobility up to 9.7 x 10 (4) cm(2) V (1) s (1) and on/off ratio of 10(4). (C) 2012 Elsevier B.V. All rights reserved.

Hierarchical artificial immune system for crop stage classification

This paper presents a new hierarchical clustering algorithm for crop stage classification using hyperspectral satellite image. Amongst the multiple benefits and uses of remote sensing, one of the important application is to solve the problem of crop stage classification. Modern commercial imaging satellites, owing to their large volume of satellite imagery, offer greater opportunities for automated image analysis. Hence, we propose a unsupervised algorithm namely Hierarchical Artificial Immune System (HAIS) of two steps: splitting the cluster centers and merging them. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The classification results have been compared with K-means and Artificial Immune System algorithms. From the results obtained, we conclude that the proposed hierarchical clustering algorithm is accurate.

Ferrocene-based Lewis acids and Lewis pairs: Synthesis and structural characterization

Optically active Lewis acids and Lewis pairs were synthesized and characterized by multinuclear NMR, UV/Vis spectroscopy and elemental analysis. Optical rotation measurements were carried out and the absolute configuration of the new chiral molecules confirmed by single crystal X-ray diffraction.

Synthesis and characterisation of novel alkoxycyanobiphenyl-substituted rufigallols

Microwave-assisted synthesis of novel alkoxycyanobiphenyl-substituted rufigallols are reported by systematically replacing one, two, four, five or six cyanobiphenyl-tethered alkoxy chains. The synthesis of the target compounds was challenging since classical reactions failed to produce these hybrids. Chemical structures of the hybrids were determined by H-1 nuclear magnetic resonance (NMR), C-13 NMR, infrared, ultraviolet spectroscopy and elemental analysis. The thermotropic liquid crystalline properties of the new compounds were investigated by polarising optical microscopy, differential scanning calorimetry and X-ray diffractometry.

Synthesis, morphology, optical and photocatalytic performance of nanostructured beta-Ga2O3

Fine powders of beta-Ga2O3 nanostructures were prepared via low temperature reflux condensation method by varying the pH value without using any surfactant. The pH value of reaction mixture had great influence on the morphology of final products. High crystalline single phase beta-Ga2O3 nanostructures were obtained by thermal treatment at 900 degrees C which was confirmed by X-ray diffraction and Raman spectroscopy. The morphological analysis revealed rod like nanostructures at lower and higher pH values of 6 and 10, while spindle like structures were obtained at pH = 8. The phase purity and presence of vibrational bands were identified using Fourier transform infrared spectroscopy. The optical absorbance spectrum showed intense absorption features in the UV spectral region. A broad blue emission peak centered at 441 nm due to donor-acceptor gallium-oxygen vacancy pair recombination appeared. The photocatalytic activity toward Rhodamine B under visible light irradiation was higher for nanorods at pH 10.

Crop stage classification of hyperspectral data using unsupervised techniques

The presence of a large number of spectral bands in the hyperspectral images increases the capability to distinguish between various physical structures. However, they suffer from the high dimensionality of the data. Hence, the processing of hyperspectral images is applied in two stages: dimensionality reduction and unsupervised classification techniques. The high dimensionality of the data has been reduced with the help of Principal Component Analysis (PCA). The selected dimensions are classified using Niche Hierarchical Artificial Immune System (NHAIS). The NHAIS combines the splitting method to search for the optimal cluster centers using niching procedure and the merging method is used to group the data points based on majority voting. Results are presented for two hyperspectral images namely EO-1 Hyperion image and Indian pines image. A performance comparison of this proposed hierarchical clustering algorithm with the earlier three unsupervised algorithms is presented. From the results obtained, we deduce that the NHAIS is efficient.

Contrast in luminescence characteristics (intense UV to bright visible light) of ZnO nanostructures with the variation in microstructure

We report the controlled variation of luminescence of ZnO nanostructures from intense ultraviolet to bright visible light. Deliberate addition of surfactants in the reaction medium not only leads to growth anisotropy of ZnO, but also alters the luminescence property. ZnO nanoclusters comprising of very fine particles with crystallite sizes approximate to 15-22nm were prepared in a non-aqueous medium, either from a single alcohol or from their mixtures. Introduction of the aqueous solution of the surfactant helps in altering the microstructure of ZnO nanostructure to nanorods, nanodumb-bells as well as the luminescence property. The as-prepared powder material is found to be well crystallized. Defects introduced by the surfactant in aqueous medium play an important role in substantial transition in the optical luminescence. Chromaticity coordinates were found to lie in the yellow region of color space. This gives an impression of white light emission from ZnO nanocrystals, when excited by a blue laser. Oxygen vacancy is described as the major defect responsible for visible light emission as quantified by X-ray photoelectron spectroscopy and Raman analysis.

Characterization and Space-Time Downscaling of the Inundation Extent over the Inner Niger Delta Using GIEMS and MODIS Data

The objective in this work is to develop downscaling methodologies to obtain a long time record of inundation extent at high spatial resolution based on the existing low spatial resolution results of the Global Inundation Extent from Multi-Satellites (GIEMS) dataset. In semiarid regions, high-spatial-resolution a priori information can be provided by visible and infrared observations from the Moderate Resolution Imaging Spectroradiometer (MODIS). The study concentrates on the Inner Niger Delta where MODIS-derived inundation extent has been estimated at a 500-m resolution. The space-time variability is first analyzed using a principal component analysis (PCA). This is particularly effective to understand the inundation variability, interpolate in time, or fill in missing values. Two innovative methods are developed (linear regression and matrix inversion) both based on the PCA representation. These GIEMS downscaling techniques have been calibrated using the 500-m MODIS data. The downscaled fields show the expected space-time behaviors from MODIS. A 20-yr dataset of the inundation extent at 500 m is derived from this analysis for the Inner Niger Delta. The methods are very general and may be applied to many basins and to other variables than inundation, provided enough a priori high-spatial-resolution information is available. The derived high-spatial-resolution dataset will be used in the framework of the Surface Water Ocean Topography (SWOT) mission to develop and test the instrument simulator as well as to select the calibration validation sites (with high space-time inundation variability). In addition, once SWOT observations are available, the downscaled methodology will be calibrated on them in order to downscale the GIEMS datasets and to extend the SWOT benefits back in time to 1993.

Correlation between local structural dynamics of proteins inferred from NMR ensembles and evolutionary dynamics of homologues of known structure

Conformational changes in proteins are extremely important for their biochemical functions. Correlation between inherent conformational variations in a protein and conformational differences in its homologues of known structure is still unclear. In this study, we have used a structural alphabet called Protein Blocks (PBs). PBs are used to perform abstraction of protein 3-D structures into a 1-D strings of 16 alphabets (a-p) based on dihedral angles of overlapping pentapeptides. We have analyzed the variations in local conformations in terms of PBs represented in the ensembles of 801 protein structures determined using NMR spectroscopy. In the analysis of concatenated data over all the residues in all the NMR ensembles, we observe that the overall nature of inherent local structural variations in NMR ensembles is similar to the nature of local structural differences in homologous proteins with a high correlation coefficient of .94. High correlation at the alignment positions corresponding to helical and beta-sheet regions is only expected. However, the correlation coefficient by considering only the loop regions is also quite high (.91). Surprisingly, segregated position-wise analysis shows that this high correlation does not hold true to loop regions at the structurally equivalent positions in NMR ensembles and their homologues of known structure. This suggests that the general nature of local structural changes is unique; however most of the local structural variations in loop regions of NMR ensembles do not correlate to their local structural differences at structurally equivalent positions in homologues.